A research aircraft will fly through the icy anvils of thunderstorms over a New Mexico mountain range to measure exactly how ice crystals form and grow inside these clouds. The problem is that global climate models cannot accurately predict how clouds will respond to a warming world. The equations they use for ice processes inside thunderstorm anvils—the vast, thin cloud sheets that spread out from the top of a storm—are based on physics that is less well understood than modellers would like. These anvil clouds are critical because they reflect sunlight back to space and trap heat, and small errors in how models represent their ice particles lead to large uncertainties in estimates of future global warming. If DCMEX succeeds, it will produce new, physically grounded equations for ice formation that can be plugged directly into the Met Office’s climate models. The result would be more reliable projections of how much the planet will warm as carbon dioxide rises—information that governments and industries use to plan infrastructure, coastal defences, and energy systems for decades ahead.
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The goal of the DCMEX project is to ultimately reduce the uncertainty in equilibrium climate sensi- tivity by improving the representation of microphysical processes in global models. It is the anvils produced by tropical systems in particular that contribute significantly to cloud feedbacks. The anvil radiative properties, lifetimes and areal extent are the key parameters. DCMEX will determine the extent to which these are influenced, or even controlled by the cloud microphysics including the habits, concentrations and sizes of the ice particles that make up the anvils, which in turn depend on the microphysical processes in the mixed-phase region of the cloud as well as those occurring in the anvil itself. There has been a rapid advancement in the sophistication of global climate models in recent years. Yet some of the equations used to represent microphysics processes are based on a poorer physical understanding than desired. Gettelman and Sherwood (2016), for example pointed out that there is significant spread in determining cloud feedbacks across different global models due to uncertainties in microphysical processes, such as the treatment of ice processes. Ceppi et al. (2017) also concluded that accurately representing clouds and their radiative effects in global models remains challenging partly due to the difficulty in representing the cloud microphysics, as well as the interactions between microphysics and dynamics. The microphysical and radiative processes and dynamics that control the opacity and areal coverage of tropical anvil clouds are not well represented in global climate models. DCMEX will make novel measurements of cloud microphysics in a real-world laboratory convective cloud system - both the mixed-phase region and anvil - as well as improve and test models and then apply them globally to tropical deep convective systems. We propose to deploy the FAAM aircraft along with two dual-polarisation, Doppler radars and airborne and ground-based aerosol measurements to study the deep convective clouds that form over an isolated mountain range in New Mexico. The focus will be on the formation of ice from ice nucleating particles (INPs) (primary ice production) and by processes involving existing ice particles (secondary ice particle production), such as collisions. These observations will be used to test and further refine the representation of ice processes in climate models. Our approach recognises that in order to represent cloud feedbacks accurately a model needs to represent the individual processes within the system accurately. Demonstrating that the model is able reproduce the observed evolution of these clouds is therefore a necessary condition for the accurate prediction of cloud feedbacks. The research in DCMEX will have a robust pathway from a novel field campaign to more accurate estimates of climate sensitivity. This pathway is built with four integrated parts: new observations; the use of these observations and process modelling to derive new parametrisations; the use of existing in-situ data and satellite observations of anvils in tropical deep convection to validate the model; and use of the knowledge gained to improve and test the representation of microphysics in climate models. In particular, DCMEX will build on the experience of our groups in improving microphysical representation. A seamless suite of Met Office models will be used for convection- resolving simulations and global simulations with parametrised convection. Finally, simplified climate change (imposed warmer environment) experiments will be carried out to understand the role of the different microphysical processes on cloud feedbacks.
Alan Blyth (Principal Investigator)Benjamin Murray (Co-Investigator)James McQuaid (Co-Investigator)Jennifer Fletcher (Co-Investigator)Paul Field (Co-Investigator)Ralph Burton (Co-Investigator)Steven Jonathan Boeing (Co-Investigator)
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